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Chaire de statistique mathématique

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Publications associées (83)

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Distributional Regression and Autoregression via Optimal Transport

Laya Ghodrati

We present a framework for performing regression when both covariate and response are probability distributions on a compact and convex subset of

\R^d

. Our regression model is based on the theory of optimal transport and links the conditional Fr'echet m ...

EPFL2023

Chaire de statistique mathématique

Graph Chatbot

Chattez avec Graph Search

Spectral Estimators for High-Dimensional Matrix Inference

Transportation-based functional ANOVA and PCA for covariance operators

Random matrix methods for high-dimensional machine learning models

A Geometric Unification of Distributionally Robust Covariance Estimators: Shrinking the Spectrum by Inflating the Ambiguity Set

On distributional autoregression and iterated transportation

Distributional Regression and Autoregression via Optimal Transport

Bayes-optimal Learning of Deep Random Networks of Extensive-width

Functional data analysis with rough sample paths?

Detecting whether a stochastic process is finitely expressed in a basis

Covariance Estimation for Random Surfaces beyond Separability

Spectral Estimators for High-Dimensional Matrix Inference

A Geometric Unification of Distributionally Robust Covariance Estimators: Shrinking the Spectrum by Inflating the Ambiguity Set

Distributional Regression and Autoregression via Optimal Transport

Bayes-optimal Learning of Deep Random Networks of Extensive-width

Detecting whether a stochastic process is finitely expressed in a basis

Covariance Estimation for Random Surfaces beyond Separability

Transportation-based functional ANOVA and PCA for covariance operators

On distributional autoregression and iterated transportation

Random matrix methods for high-dimensional machine learning models

Functional data analysis with rough sample paths?